The teaching is organized as follows:

Learning objectives

During the course, the main sources of official data will be studied and the main sampling techniques analyzed. The linear regression model will be introduced as one of the main statistical tools to examine survey data and for sales forecasting. Students will be provided with the cutting-edge statistical theory of sampling and linear regression model. These tools will then be applied to carry out market researches.

Prerequisites and basic notions

The course requires knowledge of the fundamental notions of descriptive statistics and statistical inference taught in the bachelor's degree programmes.

Program

Data sources and statistical information for business:
- primary and secondary data
- internal and external sources of data
- probabilistic sampling for market survey
Economic and business indicators:
- simple and composite index numbers
- turnover rates
Business forecasting:
- smoothing techniques: moving averages and exponential smoothing
- techniques for decomposing economic time series applied to business forecasting
Regression analysis:
- simple linear regression models
- multiple linear regression models
- introduction to generalised linear models (GLM)
- misspecifications of regression models
- regression on time series: spurious correlation and modelling techniques
Goodness of fit, prediction, and cross-validation of statistical models
Classification and regression trees (CART)
Model-based recursive partitioning
Lecture slides and other learning materials are available on the e-learning website.

Bibliography

Didactic methods

Frontal lectures in classroom and recorded lectures available online.

Learning assessment procedures

The assessment of learning outcomes consists in a written examination.
The examination consists of:
* fifteen short, multiple choice, or calculated questions
* two open-ended questions
* one open-ended question chosen from two available
All kinds of questions may be focussed on theoretical and methodological issues, may consist in exercises, or may require the student to discuss and analyse some practical problem using notions and tools learned throughout the course.
The teacher may require students to take an oral examination which completes the evaluation of the acquired knowledge. The final grade may be equal, higher or lower than the grade got on the written part of the exam.

Evaluation criteria

The written examination assesses the level of knowledge of the topics of the course, the mastery of technical language and the writing skills, the ability to analyse business and market data by means of the methods illustrated in the course and the ability to interpret the results of the analyses.

Criteria for the composition of the final grade

The examination score is on a 30-point scale (passing mark: 18).

Exam language

Italiano